频分MIMO雷达分解迭代稳健自适应波束形成算法

Decomposition and Iterative Robust Adaptive Beamforming Algorithm for Frequency diverse MIMO Radar

  • 摘要: 频率分集雷达因其独特的距离依赖波束特性而受到广泛关注。针对频率分集雷达稳健波束形成问题,本文建立了二维频分子孔径MIMO(FDS-MIMO)雷达阵列信号模型,理论导出了基于等效载频的权向量分解解析解,提出了一种分解迭代的稳健自适应波束形成算法。为解决距离依赖波束栅瓣导致的周期性输出信干燥比(SINR)损失的问题,进一步提出了一种沿平面阵两方向互质的频率偏置方案。仿真结果表明,与传统算法相比在导向矢量存在失配的情况下,本文所提方法能够有效抑制输出SINR周期性损失,且具有计算复杂度低,训练样本需求少,抗导向误差失配稳健性强等优点。

     

    Abstract: Frequency diverse array (FDA) radar has drawn a remarkable amount of attention owing to its particular range-dependent beampattern. In order to solve the problem of robust beamforming in frequency diverse radar, the frequency diverse subaperturing multiple-input multiple-output (FDS-MIMO) radar array signal model is established and the analytical of the weight vector decomposition is derived based on the equivalent carrier frequency. Then, a novel decomposition and iterative robust adaptive beamforming algorithm is proposed. Futhermore, the idea of applying co-prime frequency offsets along two directions of the planer array is presented to mitigate the periodic signal-to-interference plus noise ratio (SINR) loss which results from the range-dependent beampatern grating lobe. Simulation results show that the proposed methods can mitigate the periodic SINR loss, and has the advantages in computational burden, requiement of snapshots and robustness under the condition of steerig vector mismatch compared with the conventional algorithms.

     

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